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   },
   "source": [
    "# 实现保留目标区域内的内容，区域外的全涂白,俗称Cartopy的白化"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 实现保留目标区域内的内容，区域外的全涂白,俗称Cartopy的白化"
   ]
  },
  {
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   "source": [
    "# 导入需要用到的包\n",
    "import numpy as np\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import matplotlib.ticker as mticker\n",
    "import matplotlib.pyplot as plt\n",
    "import geopandas as gpd\n",
    "from cartopy.io.shapereader import Reader\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "###\n",
    "import xarray as xr\n",
    "### 白化关键包\n",
    "from matplotlib.path import Path\n",
    "from cartopy.mpl.patch import geos_to_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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       "      <th>adcode</th>\n",
       "      <th>name</th>\n",
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       "      <th>childrenNu</th>\n",
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       "      <th>0</th>\n",
       "      <td>450100</td>\n",
       "      <td>南宁市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>12</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((109.21702 23.29683, 109.22082 23.290...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>450200</td>\n",
       "      <td>柳州市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>10</td>\n",
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       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>POLYGON ((110.11620 24.46083, 110.09740 24.462...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>450300</td>\n",
       "      <td>桂林市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>17</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((111.09744 24.94089, 111.09774 24.931...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>450400</td>\n",
       "      <td>梧州市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>3</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((110.39190 24.04216, 110.40004 24.048...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>450500</td>\n",
       "      <td>北海市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((109.60765 21.90887, 109.61976 ...</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>450600</td>\n",
       "      <td>防城港市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((108.09588 22.37167, 108.10493 22.355...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>450700</td>\n",
       "      <td>钦州市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((109.60765 21.90887, 109.59418 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>450800</td>\n",
       "      <td>贵港市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((109.66223 22.66237, 109.65158 22.668...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>450900</td>\n",
       "      <td>玉林市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((109.66223 22.66237, 109.67319 22.676...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>451000</td>\n",
       "      <td>百色市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>12</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>9</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((106.57116 25.08350, 106.57839 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>451100</td>\n",
       "      <td>贺州市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((111.65485 23.83330, 111.65142 23.860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>451200</td>\n",
       "      <td>河池市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>11</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>11</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((106.57116 25.08350, 106.58768 25.085...</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>451300</td>\n",
       "      <td>来宾市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((108.91688 24.25500, 108.92579 24.256...</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>451400</td>\n",
       "      <td>崇左市</td>\n",
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       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((106.67072 22.88910, 106.66729 22.907...</td>\n",
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      "text/plain": [
       "    adcode  name center centroid  childrenNu level parent  subFeature  \\\n",
       "0   450100   南宁市   None     None          12  city   None           0   \n",
       "1   450200   柳州市   None     None          10  city   None           1   \n",
       "2   450300   桂林市   None     None          17  city   None           2   \n",
       "3   450400   梧州市   None     None           7  city   None           3   \n",
       "4   450500   北海市   None     None           4  city   None           4   \n",
       "5   450600  防城港市   None     None           4  city   None           5   \n",
       "6   450700   钦州市   None     None           4  city   None           6   \n",
       "7   450800   贵港市   None     None           5  city   None           7   \n",
       "8   450900   玉林市   None     None           7  city   None           8   \n",
       "9   451000   百色市   None     None          12  city   None           9   \n",
       "10  451100   贺州市   None     None           5  city   None          10   \n",
       "11  451200   河池市   None     None          11  city   None          11   \n",
       "12  451300   来宾市   None     None           6  city   None          12   \n",
       "13  451400   崇左市   None     None           7  city   None          13   \n",
       "\n",
       "   acroutes                                           geometry  \n",
       "0      None  POLYGON ((109.21702 23.29683, 109.22082 23.290...  \n",
       "1      None  POLYGON ((110.11620 24.46083, 110.09740 24.462...  \n",
       "2      None  POLYGON ((111.09744 24.94089, 111.09774 24.931...  \n",
       "3      None  POLYGON ((110.39190 24.04216, 110.40004 24.048...  \n",
       "4      None  MULTIPOLYGON (((109.60765 21.90887, 109.61976 ...  \n",
       "5      None  POLYGON ((108.09588 22.37167, 108.10493 22.355...  \n",
       "6      None  MULTIPOLYGON (((109.60765 21.90887, 109.59418 ...  \n",
       "7      None  POLYGON ((109.66223 22.66237, 109.65158 22.668...  \n",
       "8      None  POLYGON ((109.66223 22.66237, 109.67319 22.676...  \n",
       "9      None  MULTIPOLYGON (((106.57116 25.08350, 106.57839 ...  \n",
       "10     None  POLYGON ((111.65485 23.83330, 111.65142 23.860...  \n",
       "11     None  POLYGON ((106.57116 25.08350, 106.58768 25.085...  \n",
       "12     None  POLYGON ((108.91688 24.25500, 108.92579 24.256...  \n",
       "13     None  POLYGON ((106.67072 22.88910, 106.66729 22.907...  "
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   "source": [
    "# 读取地图shp文件，以广西为例\n",
    "shp= gpd.read_file('D:\\\\maplist\\\\province\\\\450000_full.shp',encoding='UTF-8')\n",
    "shp"
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       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (longitude: 241, latitude: 241, level: 27, time: 1)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 70.0 70.25 70.5 70.75 ... 129.5 129.8 130.0\n",
       "  * latitude   (latitude) float32 60.0 59.75 59.5 59.25 ... 0.75 0.5 0.25 0.0\n",
       "  * level      (level) int32 100 125 150 175 200 225 ... 900 925 950 975 1000\n",
       "  * time       (time) datetime64[ns] 2020-04-17T12:00:00\n",
       "Data variables:\n",
       "    d          (time, level, latitude, longitude) float32 ...\n",
       "    z          (time, level, latitude, longitude) float32 ...\n",
       "    t          (time, level, latitude, longitude) float32 ...\n",
       "    u          (time, level, latitude, longitude) float32 ...\n",
       "    v          (time, level, latitude, longitude) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-04-17 05:47:25 GMT by grib_to_netcdf-2.24.3: /opt/ecmw...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-79c88849-126c-483d-9d95-e9ae53ec0eb8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-79c88849-126c-483d-9d95-e9ae53ec0eb8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 241</li><li><span class='xr-has-index'>latitude</span>: 241</li><li><span class='xr-has-index'>level</span>: 27</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-54cddd3a-3e97-481d-a6b0-ec8433c65711' class='xr-section-summary-in' type='checkbox'  checked><label for='section-54cddd3a-3e97-481d-a6b0-ec8433c65711' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>70.0 70.25 70.5 ... 129.8 130.0</div><input id='attrs-3f8bc450-ace8-441c-89fc-58b909e2dd8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f8bc450-ace8-441c-89fc-58b909e2dd8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4a89a92-5a0a-446e-bd8b-11bd00bc852b' class='xr-var-data-in' type='checkbox'><label for='data-e4a89a92-5a0a-446e-bd8b-11bd00bc852b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 70.  ,  70.25,  70.5 , ..., 129.5 , 129.75, 130.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 59.75 59.5 ... 0.5 0.25 0.0</div><input id='attrs-ba12e1ac-af74-4635-8870-aacca89aa55f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba12e1ac-af74-4635-8870-aacca89aa55f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93a03b15-ae12-4e1e-817e-d69852166c8e' class='xr-var-data-in' type='checkbox'><label for='data-93a03b15-ae12-4e1e-817e-d69852166c8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([60.  , 59.75, 59.5 , ...,  0.5 ,  0.25,  0.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>100 125 150 175 ... 950 975 1000</div><input id='attrs-bc8654f8-f15c-4720-bd16-29b716234b44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc8654f8-f15c-4720-bd16-29b716234b44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79dfeecd-ce64-48d9-bc21-2539ee2baa61' class='xr-var-data-in' type='checkbox'><label for='data-79dfeecd-ce64-48d9-bc21-2539ee2baa61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([ 100,  125,  150,  175,  200,  225,  250,  300,  350,  400,  450,  500,\n",
       "        550,  600,  650,  700,  750,  775,  800,  825,  850,  875,  900,  925,\n",
       "        950,  975, 1000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-04-17T12:00:00</div><input id='attrs-f9d07842-6209-45e2-80b3-80d357c197ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9d07842-6209-45e2-80b3-80d357c197ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf010351-a8f9-495c-bf39-0e0596940ea6' class='xr-var-data-in' type='checkbox'><label for='data-cf010351-a8f9-495c-bf39-0e0596940ea6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-04-17T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6111e3a-6cbb-4b0c-ad53-e7e030a78e98' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a6111e3a-6cbb-4b0c-ad53-e7e030a78e98' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>d</span></div><div class='xr-var-dims'>(time, level, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c6cfbc02-5e40-440a-ba7c-f494559daaa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6cfbc02-5e40-440a-ba7c-f494559daaa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b62f3d1-f4c1-4864-83e9-951d5d894956' class='xr-var-data-in' type='checkbox'><label for='data-3b62f3d1-f4c1-4864-83e9-951d5d894956' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s**-1</dd><dt><span>long_name :</span></dt><dd>Divergence</dd><dt><span>standard_name :</span></dt><dd>divergence_of_wind</dd></dl></div><div class='xr-var-data'><pre>[1568187 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(time, level, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5b76c50e-db5b-40c5-a147-83560db6df98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b76c50e-db5b-40c5-a147-83560db6df98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fc505cb-8254-48bc-a0d7-cd5c80365ec6' class='xr-var-data-in' type='checkbox'><label for='data-9fc505cb-8254-48bc-a0d7-cd5c80365ec6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m**2 s**-2</dd><dt><span>long_name :</span></dt><dd>Geopotential</dd><dt><span>standard_name :</span></dt><dd>geopotential</dd></dl></div><div class='xr-var-data'><pre>[1568187 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(time, level, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e36de67-3f95-41dd-886f-930cabf19204' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e36de67-3f95-41dd-886f-930cabf19204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f9f2f07-d158-4c77-bd43-ba925979a73e' class='xr-var-data-in' type='checkbox'><label for='data-6f9f2f07-d158-4c77-bd43-ba925979a73e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd></dl></div><div class='xr-var-data'><pre>[1568187 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, level, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7a0c31f3-d03c-43c8-8a51-1e83a872febc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a0c31f3-d03c-43c8-8a51-1e83a872febc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38155bfb-afaf-4462-a3e7-821db8d86ba3' class='xr-var-data-in' type='checkbox'><label for='data-38155bfb-afaf-4462-a3e7-821db8d86ba3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>[1568187 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, level, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0a88a293-8106-4db6-afcc-c79b09b9b008' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a88a293-8106-4db6-afcc-c79b09b9b008' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e87601ff-84be-448e-bef1-d1bb8fccf6f0' class='xr-var-data-in' type='checkbox'><label for='data-e87601ff-84be-448e-bef1-d1bb8fccf6f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd></dl></div><div class='xr-var-data'><pre>[1568187 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-62f5100d-8623-4dbb-9b25-eecbd82d755d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-62f5100d-8623-4dbb-9b25-eecbd82d755d' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-04-17 05:47:25 GMT by grib_to_netcdf-2.24.3: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data5/adaptor.mars.internal-1650174444.9969342-22578-5-ad9c947f-3e7f-4827-b019-06cdf9efe694.nc /cache/tmp/ad9c947f-3e7f-4827-b019-06cdf9efe694-adaptor.mars.internal-1650174440.7539372-22578-8-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (longitude: 241, latitude: 241, level: 27, time: 1)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 70.0 70.25 70.5 70.75 ... 129.5 129.8 130.0\n",
       "  * latitude   (latitude) float32 60.0 59.75 59.5 59.25 ... 0.75 0.5 0.25 0.0\n",
       "  * level      (level) int32 100 125 150 175 200 225 ... 900 925 950 975 1000\n",
       "  * time       (time) datetime64[ns] 2020-04-17T12:00:00\n",
       "Data variables:\n",
       "    d          (time, level, latitude, longitude) float32 ...\n",
       "    z          (time, level, latitude, longitude) float32 ...\n",
       "    t          (time, level, latitude, longitude) float32 ...\n",
       "    u          (time, level, latitude, longitude) float32 ...\n",
       "    v          (time, level, latitude, longitude) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-04-17 05:47:25 GMT by grib_to_netcdf-2.24.3: /opt/ecmw..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds=xr.open_dataset(r\"D:\\DATA\\adata\\2020-4-17.nc\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# 读取1000hPa的气温\n",
    "t = ds['t'][0,:,:,:].loc[1000,:,:]\n",
    "lon=t['longitude'].data\n",
    "lat=t['latitude'].data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig= plt.figure(figsize=(9,6))\n",
    "ax=fig.subplots(1,1,subplot_kw={'projection':ccrs.PlateCarree()})\n",
    "ax.coastlines('50m')\n",
    "# ax.add_feature(cfeature.RIVERS)\n",
    "ax.add_geometries(Reader('D:\\\\maplist\\\\province\\\\450000_full.shp').geometries(),ccrs.PlateCarree(),facecolor='none', edgecolor='b', linewidth=0.8)\n",
    "ax.set_extent([100,118,15,31])\n",
    "colorbar=ax.contourf(lon,lat,t,transform=ccrs.PlateCarree())\n",
    "# 坐标轴设置\n",
    "tick = ax.gridlines(draw_labels=True, linestyle=':', linewidth=0.3, x_inline=False, y_inline=False, color='k')\n",
    "tick.top_labels = True  ##打开上面的经纬度标签\n",
    "tick.right_labels = True ###打开右边\n",
    "tick.xformatter = LONGITUDE_FORMATTER\n",
    "tick.yformatter = LATITUDE_FORMATTER\n",
    "tick.xlocator = mticker.FixedLocator(np.arange(100, 118, 1))\n",
    "tick.ylocator = mticker.FixedLocator(np.arange(15, 31, 1))\n",
    "tick.xlabel_style = {'size': 7}\n",
    "tick.ylabel_style = {'size': 7}\n",
    "## 关键操作：生成裁剪路径\n",
    "path_clip =Path.make_compound_path(*geos_to_path(shp['geometry'].to_list()))\n",
    "## 关键操作：将裁剪路径应用到图层\n",
    "for collection in colorbar.collections:\n",
    "    collection.set_clip_path(path_clip,transform=ax.transData)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<shapely.geometry.polygon.Polygon at 0x25c7f3e0460>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c0137d9c0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c0137df60>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c7f3b7580>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c7f3b66e0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c7f3b5840>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013bfe50>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013a1030>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013bfeb0>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1c90>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1cc0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1c60>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d14b0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d13f0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c0137db70>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c0137db40>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1f90>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d2380>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d21a0>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d21d0>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d24a0>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d2080>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1bd0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1b70>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1ae0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1b10>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1a80>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1a50>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d19f0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d19c0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1960>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1900>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d18a0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1870>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1840>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d13c0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1810>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d29e0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2200>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d1f30>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d1360>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d17b0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2230>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2170>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2290>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d22c0>,\n",
       " <shapely.geometry.multipolygon.MultiPolygon at 0x25c013d22f0>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2110>,\n",
       " <shapely.geometry.polygon.Polygon at 0x25c013d2260>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 把多个shp文件的地理区域添加到白化区域中\n",
    "##广西\n",
    "shp= gpd.read_file('D:\\\\maplist\\\\province\\\\450000_full.shp',encoding='UTF-8')\n",
    "##广东\n",
    "shp1=gpd.read_file('D:\\\\maplist\\\\province\\\\440000_full.shp',encoding='UTF-8')\n",
    "##湖南\n",
    "shp2=gpd.read_file('D:\\\\maplist\\\\province\\\\430000_full.shp',encoding='UTF-8')\n",
    "## 把这些数据添加到一个列表下即可\n",
    "shplist=shp['geometry'].to_list()+shp1['geometry'].to_list()+shp2['geometry'].to_list()\n",
    "shplist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig= plt.figure(figsize=(9,6))\n",
    "ax=fig.subplots(1,1,subplot_kw={'projection':ccrs.PlateCarree()})\n",
    "ax.coastlines('50m')\n",
    "# 经纬度格式，把0经度设置不加E和W\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=False)\n",
    "lat_formatter = LatitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "ax.add_geometries(Reader('D:\\\\maplist\\\\province\\\\430000_full.shp').geometries(), ccrs.PlateCarree(),\n",
    "                  facecolor='none', edgecolor='k', linewidth=0.8)##湖南\n",
    "ax.add_geometries(Reader('D:\\\\maplist\\\\province\\\\440000_full.shp').geometries(), ccrs.PlateCarree(),\n",
    "                  facecolor='none', edgecolor='r', linewidth=0.8)##广东\n",
    "ax.add_geometries(Reader('D:\\\\maplist\\\\province\\\\450000_full.shp').geometries(), ccrs.PlateCarree(),\n",
    "                  facecolor='none', edgecolor='b', linewidth=0.8)##广西\n",
    "# 添加坐标轴\n",
    "ax.set_xticks(np.arange(104, 118, 1), crs=ccrs.PlateCarree())\n",
    "ax.set_yticks(np.arange(20, 31, 1), crs=ccrs.PlateCarree())\n",
    "## 经纬度格式，把0经度设置不加E和W\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=False)\n",
    "lat_formatter = LatitudeFormatter(auto_hide=False)\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "# 设置刻度大小\n",
    "ax.tick_params(axis='y',labelsize=7)\n",
    "ax.tick_params(axis='x',labelsize=10)\n",
    "# tick = ax.gridlines(draw_labels=True, linestyle=':', linewidth=0.3, x_inline=False, y_inline=False, color='k')\n",
    "# tick.top_labels = True  ##打开上面的经纬度标签\n",
    "# tick.right_labels = True ###打开右边\n",
    "# tick.xformatter = LONGITUDE_FORMATTER\n",
    "# tick.yformatter = LATITUDE_FORMATTER\n",
    "# tick.xlocator = mticker.FixedLocator(np.arange(104, 118, 1))\n",
    "# tick.ylocator = mticker.FixedLocator(np.arange(20, 31, 1))\n",
    "# tick.xlabel_style = {'size': 7}\n",
    "# tick.ylabel_style = {'size': 7}\n",
    "ax.set_extent([104,118,20,31],ccrs.PlateCarree())\n",
    "colorbar=ax.contourf(lon,lat,t,transform=ccrs.PlateCarree())\n",
    "\n",
    "## 关键操作：生成裁剪路径\n",
    "path_clip =Path.make_compound_path(*geos_to_path(shplist))\n",
    "## 关键操作：将裁剪路径应用到图层\n",
    "for collection in colorbar.collections:\n",
    "    collection.set_clip_path(path_clip,transform=ax.transData)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
